{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "60aec9d8-e500-441f-a010-24e48c38f20f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain_openai import ChatOpenAI\n",
    "from langchain.prompts import ChatPromptTemplate\n",
    "from dotenv import load_dotenv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "cb8adc1b-e0be-487c-a3c3-966940c94d1e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "load_dotenv()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "105366ec-e041-429b-8c98-79789feae3dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "llm = ChatOpenAI(temperature=0.0, model=\"qwen2.5-72b-instruct\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ff767e3d-770d-4770-83e8-da37ba4dafdc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'When you ask about my \"prompt,\" it seems like you\\'re asking about the input or the instruction that I respond to. In this context, my prompt is the message or question you provide to me, which I then analyze and respond to based on my training and capabilities. For example, if you ask me a question about technology, my prompt is that question, and I will do my best to provide a helpful and accurate answer. If you have a specific prompt or question in mind, feel free to share it, and I\\'ll do my best to assist you!'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "llm.invoke(\"what is your prompt\").content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a95a9c7c-c6a5-4150-a6b9-0cdda30682c9",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
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